1. Bioinformatics and Sequencing Relevant to SolCAP
C. Robin Buell
Department of Plant Biology
Michigan State University
East Lansing MI 48824

2. An Overview of DNA Sequencing

3. Prokaryotic DNA Plasmid
DNA occurs in long pieces called chromosomes. Chromosomes consist of the DNA and proteins. The DNA is tightly coiled. To see the DNA better this picture shows the DNA uncoiled. DNA exits as a double-helix. Untwisting the double-helix enables us to see it’s chemical structure.

4. Eukaryotic DNA
DNA occurs in long pieces called chromosomes. Chromosomes consist of the DNA and proteins. The DNA is tightly coiled. To see the DNA better this picture shows the DNA uncoiled. DNA exits as a double-helix. Untwisting the double-helix enables us to see it’s chemical structure.

5. DNA Structure
The two strands of a DNA molecule are held together by weak bonds (hydrogen bonds) between the nitrogenous bases, which are paired in the interior of the double helix.
The two strands of DNA are antiparallel; they run in opposite directions. The carbon atoms of the deoxyribose sugars are numbered for orientation.
The uprights of this “ladder” are alternating molecules of a deoxyribose sugar (the blue pentagons) and a phosphate molecule (the yellow circles). The rungs of the “ladder” are the nitrogen bases: adenine, cytosine, guanine, and thymine. We abbreviate these base names as A, C, G, and T.
Adenine only forms a bond with Thymine. Cytosine only bonds with Guanine.
DNA easily splits apart up the middle of the ladder. Hydrogen bonds are easy to break. It does this naturally when it makes a copy of itself (replicates). Raising the temperature of the DNA will also cause it to come apart (denature).
We take advantage of these properties of DNA to discover the order of the bases (sequencing).

6. Sequencing DNA
The goal of sequencing DNA is to tell the order of the bases, or nucleotides, that form the inside of the double-helix molecule.
High throughput sequencing methods
-Sanger/Dideoxy
-Next Generation (NextGen)

7. Whole Genome Shotgun Sequencing
Start with a whole genome
Shear the DNA into many different, random segments.
Sequence each of the random segments.
Then, put the pieces back together again in their original order using a computer
For now just think of a BAC as part of a genome.

9. SEQUENCER OUTPUT ASSEMBLE FRAGMENTS Fill in any gaps Annotate genes
TAGCTAGC
AGCTAGC
AGCTAGGCTC
AGCTCGCTAGCTAGCTAGCTAGCTAGGCTC
AGCTCGCTA
TAGCTAGCTA
CTAGCTAGCTAGGCTC
GCTAGCTAGCT
CTCGCTAGCTAG
AGCTCGCTAGCTA
GCTAGCTAGC
Gene 1
Gene 2
Gene 3……
Fill in any gaps
Annotate genes

10. Theory Behind Shotgun Sequencing
Haemophilus influenzae 1.83 Mb base
Coverage unsequenced (%)
1X 37%
2X 13%
5X 0.67%
6X 0.25
7X 0.09%
For 1.83 Mb genome, 6X coverage is Mb of sequence, or 22,000 sequencing reactions, clones ( kb insert), 500 bp average read.

11. Sanger Dideoxy Sequencing reactions
-Initial dideoxy sequencing involved use of radioactive dATP and 4 separate reactions (ddATP, ddTTP, ddCTP, ddGTP) & separation on 4 separate lanes on an acrylamide gel with detection through autoradiogram
-New techologies use 4 fluorescently labeled bases and separation on capillaries and detection through a CCD camera

12. Sanger Dideoxy DNA sequencing

13. Data Analysis An chromatogram is produced and the bases are called
Software assign a quality value to each base
Phred & TraceTuner
Read DNA sequencer traces
Call bases
Assign base quality values
Write basecalls and quality values to output files.
JTrace and Phred softwares call the bases according to the peaks in the chromatogram and assign a quality value for each of the bases called.

14. GOOD
BAD

15. 454 Genome Sequencing System
Library prep, amplification and sequencing: 2-4 days
Single sample preparation from bacterial to human genomic DNA
Single amplification per genome with no cloning or cloning artifacts
Picoliter volume molecular biology
400 Mb per run (4-5 hr); less than $ 15,000 per run
Read lengths bases; new Titanium platform, 400 Mb per run, bases per reads
Massively parallel imaging, fluidics and data analysis
Requires high genome coverage for good assembly
Error rate of 1-2%
Problem with homopolymers

16. 454-Pyrosequencing Perform emulsion PCR Construct
Depositing DNA Beads into the PicoTiter™Plate
Construct
Single stranded adaptor liagated DNA
Sequencing by Synthesis:
Simultaneous sequencing of the entire genome in hundreds of thousands of picoliter-size wells
Pyrophosphate signal generation

17. Solexa/lIlumina Sequencing
Sequencing by synthesis (not chain termination)
Generate up to 12 Gb per run

19. Other “Next Generation” Sequencing Technologies
SoLiD by Applied Biosystems- short reads (~25-75 nucleotides)
Helicos- short reads (<50 nucleotides)
Pacific Biosystems-LONG reads (several kilobases)

20. Potato Wheat: Rice: 430 Mb 850 Mb 16,000 Mb 5 Mb
How much sequences are needed to assemble a eukaryotic genome?
-Depends on the genome size of the organism (genes plus repeats), ploidy level, heterozygosity, desired quality
Potato
850 Mb
Wheat:
16,000 Mb
Rice: 430 Mb
5 Mb
Arabidopsis
130 Mb
John Doe
2,500 Mb

21. Eukaryotic Genomes and Gene Structures
Intergenic
Region

22. Expressed Sequence Tags (ESTs): Sampling the Transcriptome and Genic Regions
What is an EST?
single pass sequence from cDNA
specific tissue, stage, environment, etc.
pick individual clones T7 T3
template prep
cDNA library in E.coli
Insert in
pBluescript
Multiple tissues, states..
with enough sequences, can ask quantitative questions

23. Uses of EST sequencing:
-Gene discovery
-Digital northerns/insights into transcriptome
-Genome analyses, especially annotation of genomic DNA
-SNP discovery in genic regions
Issues with EST sequencing:
-Inherent low quality due to single pass nature
-Not 100 % full length cDNA clones
-Redundant sequencing of abundant transcripts
Address through
clustering/
assembly to build
consensus sequences
= Gene Index,
Unigene Set,
Transcript Assembly

24. Locus/Gene
Gene models
Full length cDNAs
Expressed Sequence Tags

25. Types of Genomic/DNA-based Diagnostic Markers
Restriction Fragment Length Polymorphisms (RFLPs)
Random Amplification of Polymorphic DNA (RAPDs)
Cleaved Amplified Polymorphisms (CAPs)
Amplified Fragment Length Polymorphisms (AFLPs)
Simple Sequence Repeats (SSRs; microsatellites)
Single Nucleotide Polymorphisms (SNPs)

26. -Look for size polymorphisms
SSRs
-Specific primers that flank simple sequence repeat (mono-, di-, tri-, tetra-, etc) which has a higher likelihood of a polymorphism
-Amplify genomic DNA
-Separate on gel
-Look for size polymorphisms

27. SSRs
-Computational prediction of SSRs in potato transcriptome data -

28. -Detect mismatch (many methods for this)
SNPs
-Specific primers
-Amplify genomic DNA
-Detect mismatch (many methods for this)

29. Potato SNPs: Intra-varietal and inter-varietal
-Bulk of sequence data from ESTs (Sanger derived)
-Use computational methods to identify SNPs within existing potato ESTs -

30. Illumina Paired End RNA-Seq
Potato Varieties: Atlantic, Premier, Snowden
Two Paired End RNA-Seq runs were performed.
Reads are 61bp long
Insert sizes:
Atlantic: 350bp
Premier: 300bp
Snowden: 300bp
Paired End Sequencing is carried out by an Illumina module that regenerates the clusters after the first run and sequences the clusters from the other end.

31. Velvet Assemblies of Potato Illumina Sequences
With a read length of 31 and a minimum contig length of 150bp:
Atlantic:
45214 contigs
Premier:
54917 contigs
Snowden:
58754 contigs

32. Sequence quality: Viewing a Atlantic potato
contig from the Velvet assembly

33. Identify intra-varietal SNPs
Query
SNPs
Filtered SNPs
Atlantic Asm
224748
150669
Premier Asm
265673
181800
Snowden Asm
258872
166253
A/C SNP

34. Hawkeye Viewer – Visualizing SNPs
G/T SNP

35. Analyses in progress
SNP Identification:
-Identify inter-varietal SNPs using draft genome sequence from S. phureja
-Identify only biallelic SNPs
-Identify high confidence SNPs
-Identify SNPs that meet Infinium design requirements
SNP Selection:
-Annotate transcripts for gene function
-Identify candidate genes within SNP set